4.6 Article

Mist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System

期刊

SENSORS
卷 22, 期 21, 页码 -

出版社

MDPI
DOI: 10.3390/s22218500

关键词

cyber-physical human-centered system; CPHS; human-in-the-loop; IIoT; edge computing; mist computing; sustainability; smart manufacturing; Industry 5; 0; digital twin

资金

  1. Norte Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) [Norte-01-0145-FEDER-000043]
  2. Xunta de Galicia [ED431G 2019/01]
  3. [ED431C 2020/15]
  4. [PID2020-118857RA]
  5. [MCIN/AEI/10.13039/501100011033]

向作者/读者索取更多资源

This article discusses the concepts and design requirements of Cyber-Physical Human-centered Systems (CPHSs) for Industry 5.0, and analyzes the latest developments in CPHSs. It also highlights the challenges in developing CPHSs and presents a real-world use case to illustrate the concepts. The article concludes with specific guidelines for future developers and managers to overcome challenges in deploying the next generation of CPHSs for smart and sustainable manufacturing.
While many companies worldwide are still striving to adjust to Industry 4.0 principles, the transition to Industry 5.0 is already underway. Under such a paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerged to leverage operator capabilities in order to meet the goals of complex manufacturing systems towards human-centricity, resilience and sustainability. This article first describes the essential concepts for the development of Industry 5.0 CPHSs and then analyzes the latest CPHSs, identifying their main design requirements and key implementation components. Moreover, the major challenges for the development of such CPHSs are outlined. Next, to illustrate the previously described concepts, a real-world Industry 5.0 CPHS is presented. Such a CPHS enables increased operator safety and operation tracking in manufacturing processes that rely on collaborative robots and heavy machinery. Specifically, the proposed use case consists of a workshop where a smarter use of resources is required, and human proximity detection determines when machinery should be working or not in order to avoid incidents or accidents involving such machinery. The proposed CPHS makes use of a hybrid edge computing architecture with smart mist computing nodes that processes thermal images and reacts to prevent industrial safety issues. The performed experiments show that, in the selected real-world scenario, the developed CPHS algorithms are able to detect human presence with low-power devices (with a Raspberry Pi 3B) in a fast and accurate way (in less than 10 ms with a 97.04% accuracy), thus being an effective solution (e.g., a good trade-off between cost, accuracy, resilience and computational efficiency) that can be integrated into many Industry 5.0 applications. Finally, this article provides specific guidelines that will help future developers and managers to overcome the challenges that will arise when deploying the next generation of CPHSs for smart and sustainable manufacturing.

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